Question

系统配置： 作业系统：Windows 10 的Python版本：3.7 Spark版本：2.4.4 SPARK_HOME：C：\ spark \ spark-2.4.4-bin-hadoop2.7

问题我正在使用PySpark在数据帧中一行的所有列上进行并行计算。我将Pandas数据框转换为Spark数据框。在spark数据帧上，执行映射转换和收集动作。在执行收集操作时，弹出带有OSError的Py4J错误。错误在导入sklearn语句和训练有素的分类器（ML模型）中出现。

代码段

from sklearn.neural_network.multilayer_perceptron import MLPClassifier
classifier=MLPClassifier()
classifier.fit(x_train, y_train)

def func1(rows,trained_model=classifier):
    items = rows.asDict()
    row = pd.Series(items)
    output = func2(row,trained_model) # Consumes pandas series in other file having import sklearn statement
    return output

spdf=spark.createDataFrame(pandasDF)
result=spdf.rdd.map(lambda row:func1(row)).collect()

错误

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-33-0bfb9d088e2d> in <module>
----> 1 result=spdf.rdd.map(lambda row:clusterCreation(row)).collect()
      2 print(type(result))
.
.
.
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 2.0 failed 1 times, most recent failure: Lost task 2.0 in stage 2.0 (TID 5, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 364, in main
  File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 71, in read_command
  File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 580, in loads
    return pickle.loads(obj, encoding=encoding)
.
.
.
 File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\ensemble\__init__.py", line 7, in <module>
    from .forest import RandomForestClassifier
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\ensemble\forest.py", line 53, in <module>
    from ..metrics import r2_score
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\metrics\__init__.py", line 7, in <module>
    from .ranking import auc
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\metrics\ranking.py", line 35, in <module>
    from ..preprocessing import label_binarize
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\preprocessing\__init__.py", line 6, in <module>
    from ._function_transformer import FunctionTransformer
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\preprocessing\_function_transformer.py", line 5, in <module>
    from ..utils.testing import assert_allclose_dense_sparse
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\utils\testing.py", line 718, in <module>
    import pytest
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\pytest.py", line 6, in <module>
    from _pytest.assertion import register_assert_rewrite
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\__init__.py", line 6, in <module>
    from _pytest.assertion import rewrite
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\rewrite.py", line 20, in <module>
    from _pytest.assertion import util
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\util.py", line 5, in <module>
    import _pytest._code
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\_code\__init__.py", line 2, in <module>
    from .code import Code  # noqa
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\_code\code.py", line 11, in <module>
    import pluggy
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\pluggy\__init__.py", line 16, in <module>
    from .manager import PluginManager, PluginValidationError
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\pluggy\manager.py", line 6, in <module>
    import importlib_metadata
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 466, in <module>
    __version__ = version(__name__)
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 433, in version
    return distribution(package).version
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 406, in distribution
    return Distribution.from_name(package)
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 176, in from_name
    dist = next(dists, None)
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 362, in <genexpr>
    for path in map(cls._switch_path, paths)
  File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 377, in _search_path
    if not root.is_dir():
  File "C:\Users\rkagr\Anaconda3\lib\pathlib.py", line 1351, in is_dir
    return S_ISDIR(self.stat().st_mode)
  File "C:\Users\rkagr\Anaconda3\lib\pathlib.py", line 1161, in stat
    return self._accessor.stat(self)
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'C:\\C:\\spark\\spark-2.4.4-bin-hadoop2.7\\jars\\spark-core_2.11-2.4.4.jar'

MCVE 该MCVE定义了仅返回与字典相同的输入行的函数，而原始代码经过一些处理后返回了字典。

import findspark

findspark.init()
findspark.find()

import pyspark
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
conf = SparkConf().setAppName('MRC').setMaster('local[2]')
sc = SparkContext.getOrCreate(conf=conf)
spark = SparkSession.builder.getOrCreate()

import sklearn
import sklearn.datasets
import sklearn.model_selection
import sklearn.ensemble

iris = sklearn.datasets.load_iris()
train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(iris.data, iris.target, train_size=0.80)

classifier = sklearn.ensemble.RandomForestClassifier()
classifier.fit(train, labels_train)

import pickle
path = './random_classifier.mdl'
pickle.dump(classifier, open(path,'wb'))

import pandas as pd
pddf=pd.DataFrame(test)
spdf=spark.createDataFrame(pddf)

def clusterCreation(rows,classifier_path):
    items = rows.asDict()
    row = pd.Series(items)
    with open(classifier_path,'rb') as fp:
        classifier = pickle.load(fp)
        print(classifier)
    return items

result=spdf.rdd.map(lambda row:clusterCreation(row,classifier_path=path)).collect()
print(result)

Answer 1

我遇到了包含C:\\C:\\的文件路径的相同问题。我在https://github.com/Ibotta/sk-dist/issues/30中发现了一个讨论，该讨论表明pytest中使用的scikit-learn可能存在问题。在scikit-learn版本0.21.3中报告了该问题。我将scikit-learn软件包升级到0.22.1（通过升级到Anaconda 2020.02），错误消失了。

我的环境是Windows 10，Spark 2.4.5，Anaconda 2020.02（包含scikit-learn 0.22.1）。请注意，较旧的Anaconda版本2019.10包含scikit-learn版本0.21.3。

Jupyter Notebook PySpark OSError [WinError 123]文件名，目录名称或卷标签语法不正确：

1 个答案: